112 postdoc-computational-fluid-dynamics Postdoctoral research jobs at University of Washington
Sort by
Refine Your Search
-
, Fisheries Science, Biology, Zoology, Biological Oceanography, Mathematics, Statistics, Computer Science, or related discipline Knowledge of modeling ecosystem and/or social network dynamics Strong
-
well as with neuro-related industries. Job Description Primary Duties & Responsibilities: Information on being a postdoc at WashU in St. Louis can be found at https://postdoc.wustl.edu/prospective-postdocs-2
-
Primary Duties & Responsibilities: Information on being a postdoc at WashU in St. Louis can be found at https://postdoc.wustl.edu/prospective-postdocs-2/ . Trains under the supervision of a faculty mentor
-
under supervision, with the goal of establishing an independent research program and career path. The postdoc will be based at the University of Washington – Seattle Campus. The preferred start date is
-
technologies, computational genomics, functional assays, and integrated data analysis. We are seeking a highly motivated Postdoctoral Researcher who shares our passion for solving foundational problems in human
-
gels, and protein production and purification. Job Description Primary Duties & Responsibilities: Information on being a postdoc at WashU in St. Louis can be found at https://postdoc.wustl.edu
-
Position Summary The Foltz lab works at the intersection of translational immunology and computational biology. We study mechanisms of response and resistance to natural killer (NK) cell therapies
-
skills to join our effort and generate novel insights of neurodegeneration with this unique dataset, while working in a highly dynamic multidisciplinary and collaborative environment. Will join a large
-
Position Summary The Ghanbarpour Laboratory, located in the Department of Biochemistry and Molecular Biophysics at WashU Medicine, is now recruiting for a highly motivated Postdoc. Our research is
-
about exploring and applying new statistical, computational, or machine learning techniques to astronomical data sets, and extending current methodology to be applicable in the era of big data. Looking